:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Chen, Yikang, Du, Dehui, Tian, Lili
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2410.13914
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Exogenous Isomorphism for Counterfactual Identifiability
by: Chen, Yikang, et al.
Published: (2025)

Causal Discovery via Quantile Partial Effect
by: Chen, Yikang, et al.
Published: (2025)

CIER: A Novel Experience Replay Approach with Causal Inference in Deep Reinforcement Learning
by: Wang, Jingwen, et al.
Published: (2024)

Counterfactual identifiability beyond global monotonicity: non-monotone triangular structural causal models
by: Tan, Pengcheng, et al.
Published: (2026)

Spatio-temporal Value Semantics-based Abstraction for Dense Deep Reinforcement Learning
by: Nie, Jihui, et al.
Published: (2024)

Causal Bayesian Optimization via Exogenous Distribution Learning
by: Ren, Shaogang, et al.
Published: (2024)

Meta Pattern Concern Score: A Novel Evaluation Measure with Human Values for Multi-classifiers
by: Wang, Yanyun, et al.
Published: (2022)

Is Pure Exploitation Sufficient in Exogenous MDPs with Linear Function Approximation?
by: Liang, Hao, et al.
Published: (2026)

Tractable Uncertainty-Aware Meta-Learning
by: Park, Young-Jin, et al.
Published: (2022)

Tractable Representation Learning with Probabilistic Circuits
by: Braun, Steven, et al.
Published: (2025)

Learning in Markov Decision Processes with Exogenous Dynamics
by: Maran, Davide, et al.
Published: (2026)

ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection
by: Peng, Bo, et al.
Published: (2024)

Reinforcement Learning with Exogenous States and Rewards
by: Trimponias, George, et al.
Published: (2023)

Neural Tractability via Structure: Learning-Augmented Algorithms for Graph Combinatorial Optimization
by: Li, Jialiang, et al.
Published: (2025)

COSTAR: Improved Temporal Counterfactual Estimation with Self-Supervised Learning
by: Meng, Chuizheng, et al.
Published: (2023)

Tractable Sharpness-Aware Learning of Probabilistic Circuits
by: Suresh, Hrithik, et al.
Published: (2025)

Debiased Counterfactual Generation via Flow Matching from Observations
by: Dance, Hugh, et al.
Published: (2026)

Enhancing Treatment Effect Estimation via Active Learning: A Counterfactual Covering Perspective
by: Wen, Hechuan, et al.
Published: (2025)

Variation Due to Regularization Tractably Recovers Bayesian Deep Learning
by: McInerney, James, et al.
Published: (2024)

Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy
by: Lin, Yingyu, et al.
Published: (2023)

Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits
by: Peharz, Robert, et al.
Published: (2020)

Positive Distribution Shift as a Framework for Understanding Tractable Learning
by: Medvedev, Marko, et al.
Published: (2026)

Malliavin Calculus for Counterfactual Gradient Estimation in Adaptive Inverse Reinforcement Learning
by: Krishnamurthy, Vikram, et al.
Published: (2026)

Conditional Counterfactual Mean Embeddings: Doubly Robust Estimation and Learning Rates
by: Anancharoenkij, Thatchanon, et al.
Published: (2026)

Counterfactual Explanation for Multivariate Time Series Forecasting with Exogenous Variables
by: Kinjo, Keita
Published: (2025)

Tractable Probabilistic Models for Investment Planning
by: A., Nicolas M. Cuadrado, et al.
Published: (2025)

Learning and Computation of $Φ$-Equilibria at the Frontier of Tractability
by: Zhang, Brian Hu, et al.
Published: (2025)

A Tractable Online Learning Algorithm for the Multinomial Logit Contextual Bandit
by: Agrawal, Priyank, et al.
Published: (2020)

Leveraging Exogenous Signals for Hydrology Time Series Forecasting
by: He, Junyang, et al.
Published: (2025)

Offline Imitation Learning with Variational Counterfactual Reasoning
by: He, Bowei, et al.
Published: (2023)

Exploiting Exogenous Structure for Sample-Efficient Reinforcement Learning
by: Wan, Jia, et al.
Published: (2024)

Scalable Counterfactual Risk Estimation for Rare Events in Longitudinal Data
by: Yin, Xiaohui, et al.
Published: (2026)

Restructuring Tractable Probabilistic Circuits
by: Zhang, Honghua, et al.
Published: (2024)

Counterfactual inference in sequential experiments
by: Dwivedi, Raaz, et al.
Published: (2022)

Abstract Counterfactuals for Language Model Agents
by: Pona, Edoardo, et al.
Published: (2025)

Characterizing Learning in Deep Neural Networks using Tractable Algorithmic Complexity Analysis
by: Bakhtiarifard, Pedram, et al.
Published: (2026)

A Rigorous, Tractable Measure of Model Complexity
by: Allerbo, Oskar, et al.
Published: (2026)

Doubly-Robust Estimation of Counterfactual Policy Mean Embeddings
by: Zenati, Houssam, et al.
Published: (2025)

Fast and Robust State Estimation and Tracking via Hierarchical Learning
by: Mclaughlin, Connor, et al.
Published: (2023)

Tractable Offline Learning of Regular Decision Processes
by: Deb, Ahana, et al.
Published: (2024)